One of the most common forms of email is provided by Email Service Providers (ESPs) such as Yahoo! Mail, Microsoft Hotmail, Google GMail, and other web-based email services. In large scale ESPs, the problem of unsolicited bulk email messages (UBE), is acute. Issues also exist with providing users a positive experience with respect to gray mail—mail which may come from legitimate advertisers that some users may want to receive while others do not. Providers use a number of techniques in an effort to shield users from receiving UBE and correctly filter grey mail.
One issue with controlling the user experience in such systems is that filtering is generally applied on a global or system wide level. Generally, global filtering is applied to all users independent of any user preference. Drawbacks to global filtering may include difficulty in choosing whether to deliver gray mail. Gray mail may be considered bulk email that users may disagree on whether the message is spam or legitimate. Such mail may come from legitimate corporate senders that users have subscribed to, but who later classify the mail as spam.
Filter training by explicit user classifications via a user interface as limits the responsiveness of a mail system due to the inherent delay in receiving the feedback from a select number of users. In addition, users are generally not inclined to repeatedly provide feedback over time, and the accuracy of such feedback varies. For example, some users may classify mail from legitimate senders for whose emails they at one time opted to receive as “spam.” Generally such feedback is not incorporated into global level filters for later use by the filter.